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<table width="100%" summary="page for boundsdata"><tr><td>boundsdata</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Example Data for the Design Functions</h2>

<h3>Description</h3>

<p>A random subsample of the simulated data used in Imai, Tingley, and
Yamamoto (2012). The data contains 1000 rows and 7 columns with no missing 
values.
</p>


<h3>Usage</h3>

<pre>
boundsdata
</pre>


<h3>Format</h3>

<p>A data frame containing the following variables, which are 
interpreted as results from a hypothetical randomized trial. See the source 
for a full description.
</p>

<dl>
<dt>out:</dt><dd><p> The binary outcome variable under the parallel design.</p>
</dd>
<dt>out.enc:</dt><dd><p> The binary outcome variable under the parallel 
encouragement design.</p>
</dd>
<dt>med:</dt><dd><p> The binary mediator under the parallel design.</p>
</dd>
<dt>med.enc:</dt><dd><p> The binary mediator under the parallel encouragement 
design.</p>
</dd>
<dt>ttt:</dt><dd><p> The binary treatment variable.</p>
</dd>
<dt>manip:</dt><dd><p> The design indicator, or the variable indicating whether the 
mediator is manipulated under the parallel design.</p>
</dd>
<dt>enc:</dt><dd><p> The trichotomous encouragement variable under the parallel 
encouragement design. Equals 0 if subject received no encouragement; 1 if 
encouraged for the mediator value of 1; and -1 if encouraged for the 
mediator value of 0.</p>
</dd>
</dl>


<h3>Details</h3>

<p>Conditioning on 'manip' = 0 will simulate a randomized trial under 
the single experiment design, where 'out' and 'med' equal observed outcome 
and mediator values, respectively.
</p>
<p>Unconditionally, using 'out', 'med', 'ttt' and 'manip' will simulate an 
experiment under the parallel design.
</p>
<p>The 'out.enc' and 'med.enc' variables represent the outcome and mediator 
values observed when subjects received the encouragement indicated in 
'enc'. Therefore, using 'out.enc', 'med.enc', 'ttt' and 'enc' will simulate 
an experiment under the parallel encouragement design.
</p>
<p>Note that all the observed responses are generated from an underlying 
distribution of potential outcomes and mediators (not shown in this 
dataset) satisfying the assumptions described in Imai, Tingley and 
Yamamoto (2012). The full simulation code is available as a companion 
replication archive for the article.
</p>


<h3>Source</h3>

<p>Imai, K., Tingley, D. and Yamamoto, T. (2012) Experimental Designs 
for Identifying Causal Mechanisms. Journal of the Royal Statistical 
Society, Series A (Statistics in Society).
</p>


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